Search

In a delay tolerant network (DTN) nodes are scattered and intermittently connected. In this network end-to-end path cannot be assumed to be available. Routing protocols in DTNs usually replicate message in the network to transmit the message toward its destination. Managing message replication and distribution, and finding appropriate relay nodes due to the lack of timely and precise information is a major challenge. Existing multi-copy routing protocols when replicate and distribute copies of message don't consider some capabilities of nodes as the power to take and carry copies, this may lead to delays in delivering the message. In this paper, we proposed a multi-step routing protocol for DTNs. In each routing step, our protocol first dynamically determines the needed number of copies and also share of nodes from these copies. It makes decisions with the help of an attribute named Replication Capability Rate (RCR). The fuzzy system provides RCR based on the capability of nodes as power and property of message as time to live. Then, protocol sprays copies until remaining single copy in the buffer of the node. Finally, the single copy of the message is exchanged between nodes according to the encounter frequency. Experiment results show that our protocol significantly decreases the average delay and keeps delivery probability high, in comparison with well-known protocols. [ABSTRACT FROM AUTHOR]

Delay-tolerant networks (DTNs) are networks where there is no immediate connection between the source and the destination. Instead, nodes in these networks use a store–carry–forward method to route traffic. However, approaches that rely on flooding the network with unlimited copies of messages may not be effective if network resources are limited. On the other hand, quota-based approaches are more resource-efficient but can have low delivery rates and high delivery delays. This paper introduces the Enhanced Message Replication Technique (EMRT), which dynamically adjusts the number of message replicas based on a node's ability to quickly disseminate the message. This decision is based on factors such as current connections, encounter history, buffer size history, time-to-live values, and energy. The EMRT is applied to three different quota-based protocols: Spray and Wait, Encounter-Based Routing (EBR), and the Destination-Based Routing Protocol (DBRP). The simulation results show that applying the EMRT to these protocols improves the delivery ratio, overhead ratio, and latency average. For example, when combined with Spray and Wait, EBR, and DBRP, the delivery probability is improved by 13%, 8%, and 10%, respectively, while the latency average is reduced by 51%, 14%, and 13%, respectively. [ABSTRACT FROM AUTHOR]

Opportunistic Delay Tolerant Networks also referred to as Opportunistic Networks (OppNets) are a subset of wireless networks having mobile nodes with discontinuous opportunistic connections. As such, developing a performant routing protocol in such an environment remains a challenge. Most research in the literature have shown that reinforcement learning-based routing algorithms can achieve a good routing performance, but these algorithms suffer from under-estimations and/or over-estimations. Toward addressing these shortcomings, in this paper, a Double Q-learning based routing protocol for Opportunistic Networks framework named Off-Policy Reinforcement-based Adaptive Learning (ORAL) is proposed, which selects the most suitable next-hop node to transmit the message toward its destination without any bias by using a weighted double Q-estimator. In the next-hop selection process, a probability-based reward mechanism is involved, which considers the node's delivery probability and the frequency of encounters among the nodes to boost the protocol's efficiency. Simulation results convey that the proposed ORAL protocol improves the message delivery ratio by maintaining a trade-off between underestimation and overestimation. Simulations are conducted using the HAGGLE INFOCOM 2006 real mobility data trace and synthetic model, showing that when time-to-live is varied, (1) the proposed ORAL scheme outperforms DQLR by 14.05%, 9.4%, 5.81% respectively in terms of delivery probability, overhead ratio and average delay; (2) it also outperforms RLPRoPHET by 16.17%, 9.2%, 6.85%, respectively in terms of delivery ratio, overhead ratio and average delay. [ABSTRACT FROM AUTHOR]

Delay-tolerant networks allow communication using store-carry-forward technique between source and destination nodes where no end-to-end connectivity exists. In case of network disconnection, messages get stored in a node and wait till the connection is restored, which could be forwarded to another node. To explore the possibility of improvement, many researchers have applied protocol based on fuzzy in DTN, but none of them proposed any solution for the situation where the node density is very low. This situation may result in low buffer availability. Hence, the nodes become unavailable for forwarding messages due to low buffer availability. In general, the remote area does not have a dense network thus, required buffer size might not be available at all the nodes for enabling communication. In this paper, we proposed a solution for the scenario where nodes cannot accept any message due to the unavailability of storage. To make communication possible, we formulated a methodology to search for the best node available in the communication range for relaying the message. The selected node is tested for buffer availability. As per negative result, it is subjected to buffer cleaning and then used for sending a message to that node. If the result is positive, the message will be sent directly to the relay node. A Fuzzy logic system is used for relay node selection and buffer cleaning process. ONE simulator has been adopted for simulating the environment and the simulation results indicate that the proposed technique enhanced the network's performance. [ABSTRACT FROM AUTHOR]

Summary: In delay‐tolerant networks (DTN), node connection time and message transmission time are two important influencing factors that can improve the delivery rate. In this paper, we first define a new concept called communication capability (CC) and then apply this concept to the delivery predictability formulation in Prophet and improve it. Then, in Prophet, the selection of relay nodes relies only on the delivery predictability and ignores the caching and forwarding capability of the node. Therefore, we combine delivery predictability, buffering, and forwarding capability to develop a new adaptive relay node selection strategy. Subsequently, we define two metrics called message priority (MP) and message strength (MS). The node forwards messages sequentially based on message priority and discards messages based on message strength. Finally, we present a probabilistic routing algorithm based on node communication capability and message strength (CAMS). The simulation results show that compared with traditional routing algorithms, the CAMS can effectively improve the message delivery rate, reduce the overhead ratio, and keep average hop counts low. [ABSTRACT FROM AUTHOR]

In the recent era, security is the major problem in sensor networks. Wireless sensor networks (WSNs) are mostly used for various real-world applications. However, WSNs face a lot of insider and outsider attacks, and it is complex to identify and protect towards insider attacks. Generally, an insider attack, in which the intruders choose several received data packets to drop, threatens the clustered WSNs. This situation has occurred because of the unattended clustered environments in the network. To overcome this problem, this paper proposes a trustable and secure routing scheme using two-stage security mechanism, and dual assurance scheme, for selecting the node and securing the data packet for WSNs. Both schemes are based on Active Trust to protect several kinds of attacks, such as black hole attack, and selective forwarding attack, during routing. Therefore, this paper identifies the trusted path and provides the secure routing paths using trust and Cuckoo search algorithm. Energy is the performance parameter utilized in the proposed scheme. The experimental result proves that proposed system provides the assurance to prolong the network lifespan and the probability of secure routing path in the network. [ABSTRACT FROM AUTHOR]

This paper presents a sparse ad hoc network where multiple mobility controlled message ferries cooperate to deliver messages for stationary and disconnected wireless nodes. Unmanned Aerial Vehicles (UAVs) are utilized as message ferries with an on-the-fly mobility decision making. The multi-hop delivery of messages is enabled by efficient message forwarding and replication among UAVs to accelerate the delivery of messages. Due to lack of global knowledge in UAVs, decisions in a UAV are made based on local observations. To this end, a signaling among UAVs occurs when they visit each other on-the-air. Through signaling, a UAV updates its view from the network and applies this information to its decision makers. Trajectory aware and priority based message replication schemes are proposed in this paper to limit the number of message replications and to decrease the delay of message delivery. The results show that the multi-hop delivery of messages in a message ferry network by message forwarding and replication among UAVs accelerates the delivery of messages comparing with a pure message ferrying scheme without any message forwarding. The proposed trajectory aware message replication scheme performs as good as the unlimited message replication scheme while decreasing the buffer length in UAVs. Moreover, the priority based message replication scheme in UAVs speeds up the delivery of high priority messages without any adverse impact on low priority messages. [ABSTRACT FROM AUTHOR]

Immediately after the occurrence of a natural disaster, communication infrastructures used in daily life become temporarily unavailable. Under such a situation, intermittently connected mobile ad hoc networks (MANETs) play an important role in providing post-disaster networking. While previous studies on such networks have mainly focused on one-to-one messaging applications, the importance of monitoring applications has become increasingly important in recent years. For monitoring applications, the key performance measure is given by the freshness of the information, rather than the traditional delay characteristics. In this paper, we present a mathematical analysis of the age of information (AoI) for intermittently connected MANETs, which captures the information freshness of monitoring applications. We further investigate basic principles in the network design based on the analytical results obtained. In particular, we discuss the AoI-energy tradeoff from different perspectives of source and relay nodes. [ABSTRACT FROM AUTHOR]

A Delay Tolerant Network (DTN) is a network capable of handling long delays and data loss efficiently in various challenged scenarios and environments. Owing to the mentioned challenges, it becomes crucial to study how the routing protocols are designed to adapt in such networks. Currently, the research in this domain is focused on the improving the data delivery ratio and minimizing delays in the routing protocols. This paper reviews state-of-the-art routing protocols for Delay Tolerant Networks (DTNs) as well as performs their comparative analysis. DTN routing protocols are grouped into four categories viz encounter based, time based, infrastructure based and hybrid & others. This categorization depends on the information they use for relay selection routing. We have also discussed some of the inherent drawbacks such as energy consumption, delivery rates and buffer constraints of the existing routing algorithms. We have also conducted an empirical analysis and observed the performance of the most popular existing algorithms of encounter and time based category. This paper offers a widespread study of the routing protocols with their pros and cons. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the impact of delaying delay-tolerant calls under certain conditions in cellular networks. We propose to queue the call if the user agrees when the terminal has bad radio conditions and the system is loaded. The call is served as soon as radio conditions become good or the current load goes below a given threshold. We model the system as a continuous-time Markov chain, which allows us to compute the blocking probability, the mean waiting time and the mean service time. Numerical results show that when the proportion of users with delay tolerance is 20%, the system can bear 16% more calls with the same blocking probability, and 113% more calls if 80% of users are delay tolerant. [ABSTRACT FROM AUTHOR]

Mobile Opportunistic Networks (MONs) are characterized by intermittent connectivity with long isolation period, and nodes following redundant transmissions for reliable message delivery. This often leads to unnecessary buffer occupancy, preventing new messages from getting replicated due to small contact duration and low bandwidth, or leading to packet drop under constrained buffer. Although attempts have been made to mitigate buffer congestion, the existing schemes are localized, are slow to react, or are specific to a routing scheme. Moreover, they rely on message exchanges to obtain buffer state/occupancy, thereby incurring additional overhead. In this paper, we first develop a generalized probabilistic forwarding model where the forwarding probability denotes the likelihood of a message to get forwarded to the encountered node. Based on the forwarding probability, we develop a congestion indicator and predict the point of congestion using the Kalman filter. Using this, a node can decide the optimal number and the exact set of messages to replicate, which leads to an optimal performance with minimal packet drop and overhead. Simulation results using a synthetic mobility model and a real-life mobility trace show that the proposed scheme outperforms the existing schemes. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Central China Normal University is the property of Huazhong Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In Opportunistic Networks, portable devices such as smartphones, tablets, and wearables carried by individuals, can communicate and save-carry-forward their messages. The message transmission is often in the short range supported by communication protocols, such as Bluetooth, Bluetooth Low Energy, and Zigbee. These devices carried by individuals along with a city's taxis and buses represent network nodes. The mobility, buffer size, message interval, number of nodes, and number of messages copied in such a network influence the network's performance. Extending these factors can improve the delivery of the messages and, consequently, network performance; however, due to the limited network resources, it increases the cost and appends the network overhead. The network delivers the maximized performance when supported by the optimal factors. In this paper, we measured, predicted, and analyzed the impact of these factors on network performance using the Opportunistic Network Environment simulator and machine learning techniques. We calculated the optimal factors depending on the network features. We have used three datasets, each with features and characteristics reflecting different network structures. We collected the real-time GPS coordinates of 500 taxis in San Francisco, 320 taxis in Rome, and 196 public transportation buses in Münster, Germany, within 48 h. We also compared the network performance without selfish nodes and with 5 % , 10 % , 20 % , and 50 % selfish nodes. We suggested the optimized configuration under real-world conditions when resources are limited. In addition, we compared the performance of Epidemic, Prophet, and PPHB++ routing algorithms fed with the optimized factors. The results show how to consider the best settings for the network according to the needs and how self-sustaining nodes will affect network performance. [ABSTRACT FROM AUTHOR]

One of the major concerns in any emergency relief operation is appropriate allocation of scarce emergency relief materials to the affected community. Due to several reasons ranging from lack of mechanism to accurately assess demand and utility of relief materials to malicious participation of some of the stakeholders, such allocation may become ad-hoc. Thus, it becomes imperative to have an unchallengeable and globally accessible record of relief requirement vis-à-vis allocation for efficient relief management. Emergency response organizations (e.g. UNICEF) have recommended the adoption of blockchain technology to create such immutable records. However, the usage of blockchain is restricted by the availability of end-to-end internet connection which may not be available in a post-disaster scenario. This paper proposes ReliefChain, a blockchain leveraged post disaster relief allocation system over delay tolerant network that works in such environments. We validate relief requirements to mitigate resource diversion, forecasting the exact demand and enumerating precise utilities of relief items. We design smart contracts for creating new transactions to upload relief requirements and allocations in the blockchain network. The proposed system executes these smart contracts to create an immutable and globally accessible record of relief requirement and allocation. Effectiveness of the proposed system is evaluated through extensive simulation in Ethereum platform. Results substantiate the efficiency of the system over a system using baseline methodologies, in terms of design parameters like shelter specific deficit and average resource deficit while not compromising the blockchain performance in terms of processing time and gas consumption even in presence of malicious forwarders. [ABSTRACT FROM AUTHOR]

In this paper, we propose an optimal multi-hop transmission scheme to maximize the end-to-end data rate from the source to the destination node in a wireless powered communication network. The frame structure for multi-hop transmission is presented to transmit multi-hop data while harvesting energy. Then, the transmission time of each node that maximizes the end-to-end transmission rate is determined through mathematical analysis in consideration of different harvested energy and link quality among nodes. We derive an optimization problem through system modeling of the considered wireless powered multi-hop transmission, and prove that there is a global optimal solution by verifying the convexity of this optimization problem. This analysis facilitates to find the optimal solution of the considered optimization problem. The proposed optimal multi-hop transmission scheme maximizes the end-to-end rate by allocating the transmission time for each node that equalizes the transmission rates of all links. [ABSTRACT FROM AUTHOR]

Summary: Opportunistic ad hoc networks (OppNets) are characterized by intermittent and infrastructure‐less connectivity among mobile nodes with limited internode communication and buffer space. Without persistent end‐to‐end routing information, replication‐based routing techniques are often used to distribute duplicate messages in OppNets, which unfortunately leads to enormous costs of transmission, storage, and energy resources. Prior replication‐based routing schemes were mainly based on several premises, for example, the availability of global network knowledge, unlimited bandwidth capacity, and homogeneous contact patterns. In this paper, we propose a quota‐based routing scheme with finite buffer management, named QRBP, regardless of these weak premises. The QRBP scheme comprises two essential functions. First, only a portion of nodes with higher mobility are delegated to carry a certain quota of message replicas and disseminate those messages to nodes with lower mobility. The message traffic can be evenly diverted to relay nodes, which reduces the transmission overhead in the network. Second, nodes can manipulate message scheduling and dropping to improve the successful delivery rate according to heuristic strategies based on several measures of the quota value, remaining time‐to‐live, and contact rate with the destination. Furthermore, our study conducts extensive simulations under both synthetic and real mobility scenarios. In terms of transmission overhead ratio and successful delivery rate, the QRBP scheme performs better than Epidemic, Spray and Wait, and Temporal Closeness and Centrality‐Based (TCCB) routing schemes, as well as common buffer management policies like Drop Oldest, Drop Newest, Drop Random, and Space‐Time Drop. [ABSTRACT FROM AUTHOR]

Information-centric networking (ICN) is a new network architecture that routes content based on names to improve transmission performance. Therefore, the efficiency of name resolution and routing becomes a critical issue in ICN. The bloom filter-based routing scheme has gained significant attention for its ability to improve the memory efficiency of routing nodes in the network, but it cannot handle the movement or deletion of content and has a high false positive rate, which increases bandwidth consumption. In this paper, we propose a cuckoo filter-based name resolution and routing method where resolution requests are forwarded through a hierarchical network structure to the node closest to the content copy as much as possible to minimize latency. This method achieves reliable content removal and allows summaries of content to be exchanged between nodes for resolution error correction and information synchronization based on a modified cuckoo filter. The simulation results show that our method can effectively reduce the number of false positives, and it can reduce the additional overhead caused by processing false positives for a large-scale network by 50% compared with the bloom filter-based scheme. [ABSTRACT FROM AUTHOR]

Geocast, which consists of delivering messages to a specific location, has become an important technique with the accelerated development of the location-based services in mobile networks. Geocast in the automotive domain is of particular interest, enabling many promising applications, such as geographic advertising, location-based traffic alerts, etc. Different from the conventional geocast algorithms focusing on the distance-based approaches, in this paper, we propose a node mobility-aware and node contact-aware geocast algorithm (GeoMobCon) for urban vehicular ad hoc networks from the delay-tolerant network perspective to better deal with the high mobility and transient connectivity issues. Different levels and aspects of vehicle mobility information and self-maintained contact information are employed, making GeoMobCon simple, scalable, and communication and computation effective. Practical issues are well considered by introducing real-world trace analysis, trace-driven simulation, and efficient buffer management. Extensive performance comparisons with other protocols have been conducted to show the advantages of GeoMobCon. [ABSTRACT FROM AUTHOR]

Opportunistic scheduling of delay-tolerant traffic has been shown to substantially improve spectrum efficiency. To encourage users to adopt delay-tolerant scheduling for capacity -improvement, it is critical to provide guarantees in terms of completion time. In this paper, we study application-level scheduling with deadline constraints, where the deadline is pre-specified by users/applications and is associated with a deadline violation probability. To address the exponentially-high complexity due to temporally-varying channel conditions and deadline constraints, we develop a novel asymptotic approach that exploits the largeness of the network to our advantage. Specifically, we identify a lower bound on the deadline violation probability, and propose simple policies that achieve the lower bound in the large-system regime. The results in this paper thus provide a rigorous analytical framework to develop and analyze policies for application-level scheduling under very general settings of channel models and deadline requirements. Further, based on the asymptotic approach , we propose the notion of Application-Level Effective Capacity region, i.e., the throughput region that can be supported subject to deadline constraints, which allows us to quantify the potential gain of application-level scheduling. Simulation results show that application-level scheduling can improve the system capacity significantly while guaranteeing the deadline constraints. [ABSTRACT FROM PUBLISHER]

Delay-tolerant networks (DTNs) consist of nodes moving around and occasionally coming into each other's proximity. During the limited proximity time, nodes can exchange data; this can result in a very slow data dissemination process that is usually governed by a replication-based mechanism. However, due to the long propagation delay and the large overhead associated with the replication approach, DTN delivery performance is neither efficient nor effective. To reduce the overhead, which becomes a critical aspect particularly when addressing a multicast scenario, infection recovery mechanisms have been proposed to control and reduce the number of packet copies circulating through the network. This, however, has the cost of decreasing the chances of delivering packets to all destinations. In this paper, adaptivity in infection recovery is addressed. This represents a viable solution to make transmission more reliable, hence delaying the activation of the infection recovery procedure, depending on the number of nodes, destinations, and the time. Moreover, we also propose to exploit an additional feature in data multicasting, i.e., socially aided data dissemination, where the packet dissemination procedure is not trivially epidemic, but rather exploits the intrinsic sociality of users and their interests to reduce the delivery overhead and speed up the multicast process. More specifically, we consider a procedure where users are not regarded as individual members of the network but can be aggregated into groups sharing interests, and their sociality helps the data dissemination procedure. Results of our analysis show that new sociality-aided adaptive recovery schemes can speed up the delivery process. [ABSTRACT FROM AUTHOR]

In this paper, we propose a heterogeneous framework to deliver smart grid (SG) data cost effectively. The data generated by distributed SG loads, and generation units should be delivered to the utility control center (UCC) within the tolerated delay, which is crucial for SG applications. To this end, a heterogeneous communication framework is proposed, where the cellular network (CN) provides ubiquitous yet expensive data transmission, and vehicle-assisted device-to-device (D2D) communications are leveraged to offload the CN by delivering the delay-tolerant SG data in a store–carry–forward fashion with low cost. To improve the offloading and cost performance of the proposed framework, we put effort in the following aspects: 1) optimal forwarding schemes to optimally select vehicles to carry and forward the data; and 2) mode selection and dynamic resource allocation to maximize the amount of data delivered by D2D communications, reduce the cost of SG data delivery, and guarantee the fairness among SG users. Simulation results are given to validate proposed approaches and demonstrate that the proposed framework is efficient in saving cost for the utility and offloading the CN. [ABSTRACT FROM AUTHOR]

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With device-to-device (D2D) communication, user equipment can share data with each other without the involvement of network infrastructures. In order to maintain the Quality of Service (QoS) and Quality of Experience (QoE) for user applications in D2D communications, most existing schemes use proactive content caching that needs to predict content popularity before making caching decisions which may result in privacy leakage, since the information of users is collected to train a deep learning-based model to predict content popularity. Therefore, it is crucial to guarantee secure data collection in machine learning-based framework. In this paper, we propose a privacy-preserving D2D caching scheme with a passive content caching strategy based on node importance, which can deliver more efficient caching and prevent the potential leakage of user privacy. The scheme is based on softwaredefined networking (SDN), in which the controller is responsible for calculating node importance of devices according to the information of requests and encounters collected by SDN switches. Base station will decide which device can establish reliable and secure communication with content requester based on historical information. The simulation results show that the proposed strategy can outperform other D2D caching strategies in terms of cache hit rate and data rate. [ABSTRACT FROM AUTHOR]

Mobile opportunistic networks (MONs) are intermittently connected networks in which a multitude of mobile devices are carried by people and packets are delivered among devices via opportunistic communications. In opportunistic networks (OppNets), messages are transmitted between nodes in an opportunistic fashion following a store, carry-and-forward approach and a routing protocol, with the hope to reach their destinations. Routing in MONs is very challenging as it must handle network partitioning, long delays, and dynamic topology. In existing routing protocols for OppNets, different parameters such as node's delivery predictability, node's mobility, distance with respect to destination, node's energy consumption, contact duration between nodes etc. are considered in the selection of the best suitable next hop to carry the message toward the destination. In this paper we have presented a routing protocol which considers the location history, access patterns of mobile user as its feature and infer the location and social relationship between the mobile users. We have a large dataset of mobile users which is simulated and simulation results show the effectiveness of geo social methods. [ABSTRACT FROM AUTHOR]

The vehicular delay-tolerant network is the real-life application based area of Delay tolerant network where communication takes place using vehicular nodes and roadside units. The topology used in vehicular networks is highly dynamic by architecture due to the use of moving vehicular nodes. It operates in such a scenario where a direct path between source and destination remains absent on the most piece of the time. In case of non-existence of connected path vehicular delay-tolerant network works opportunistically and uses the same store, carry, and forward paradigm as Delay Tolerant Network. However, the routing protocols designed for vehicular delay-tolerant network faces crucial challenges like inadequate relay node, incomplete data transfer, a large number of packet drop, and uncertain delivery time. In this research paper, we propose a novel routing strategy for the vehicular delay-tolerant network. The proposed routing strategy selects efficient vehicular relay node for complete packet transfer and intelligently reduces the packet drop for timely packet delivery. We implement the proposed routing strategy in the ONE simulator; the ONE simulator provides an opportunistic environment for nodes. We analyze the performance of the proposed strategy under various simulations results using different parameters. The results show that the proposed strategy outperforms standard routing protocols in terms of considered parameters and provide an efficient solution for the problem of disconnection. [ABSTRACT FROM AUTHOR]

In Wireless Sensor Network (WSN), because battery and energy supply are constraints, sleep scheduling is always needed to save energy while maintaining connectivity for packet delivery. Traditional schemes have to ensure high duty cycling to ensure enough percentage of active nodes and then derogate the energy efficiency. This paper proposes an RFID based non-preemptive random sleep scheduling scheme with stable low duty cycle. It employs delay tolerant network routing protocol to tackle the frequent disconnections. A low-power RFID based non-preemptive wakeup signal is used to confirm the availability of next-hop before sending packet. It eliminates energy consumption of repeated retransmission of the delayed packets. Moreover, the received wakeup signal is postponed to take effect until the sleep period is finished, and the waken node then responds to the sending node to start the packet delivery. The scheme can keep stable duty cycle and then ensure energy saving effect compared with other sleeping scheduling methods. [ABSTRACT FROM AUTHOR]

A delay-tolerant network (DTN) is a network with dynamic topology changes, network partitions and node mobility. Multi-copy routing protocols are usually adopted to overcome these characteristics. Although multi-copy routing protocols can improve the message delivery ratio and reduce the message propagation delay, they also easily exhaust the limited storage space of nodes, resulting in buffer overflows. The major task of buffer management is to determine which message will be discarded when buffer overflows happen. Determining the order of discarding messages will directly affect the performance of the network. In this paper, we propose a novel weight-based buffer management policy (NWBBMP) that divides messages in the node into a priority message queue, a high-weight message queue and a low-weight message queue. When a node receives a new message that causes a buffer overflow, the algorithm determines which queue’s messages will be discarded according to whether the current node is the destination node of the new message. Simulation results show that our algorithm outperforms traditional buffer management algorithms in terms of delivery ratio, average delay and network overhead. [ABSTRACT FROM AUTHOR]

The next generation of cellular networks (5G) will provide dense millimeter-wave backhaul architectures to wirelessly forward heterogeneous data traffic in a multihop fashion. In this paper, we present a general optimization framework for the design of delay-aware (DA) policies in multihop wireless networks, providing proportional prioritization of traffic. We develop three throughput-optimal DA algorithms (BP-DA, BPE-DA, and HD-DA) for joint dynamic routing and dynamic link-scheduling problems with good to optimal average network delay performance. Our DA framework considers both the classical back-pressure (BP) and the recent heat-diffusion (HD) algorithms, since queue back-pressure algorithms are being considered for mmWave backhauling management. We provide analytical results for the throughput-optimality of the proposed policies and average delay minimization of HD-DA within the class of DA policies. These are policies that make decisions at each timeslot based only on current channel state, current network queue sizes, and flow priorities. We discuss the applications of our proposals to backhaul management of mmWave cellular networks in light of recent works in the literature. Finally, we present extensive simulations of our proposed algorithms, which confirm the theoretical results and show how the algorithms effectively differentiate data traffic in terms of delay while satisfying flow rate requirements. [ABSTRACT FROM PUBLISHER]

Delay Tolerant Networks (DTNs) have attracted various interests these days. Since DTNs are subject to high loss rate, large delay, intermittent connection, and even no end-to-end connectivity, relay nodes, such as throwboxes, are deployed to enhance network performance. Internet-based systems have contemporaneous connectivity between location-distributed nodes, and this does not apply to DTNs. Thus, the traditional relay node deployment strategies are no longer suitable for DTNs. In this paper, we propose a novel strategy, named Connection-2 (CO2), to deploy throwboxes to enhance the fault tolerance of DTNs. CO2 constructs a 2-connected DTN using an approximation algorithm. Every mobile node in the 2-connected DTN can reach another mobile node via two or more node-disjoint paths within its mobility range. While enhancing fault tolerance, the number of throwboxes that CO2 requires is small. We conduct various experiments based on the simulation of the real Tuscaloosa bus transit system and compare its performance with two popular strategies. Experimental results show that CO2 is effective. [ABSTRACT FROM AUTHOR]

Delay tolerant networks (DTNs) are featured by unpredictable mobility patterns and easily interrupted connections. Forwarding strategy has always been the research focus in DTNs, in order to improve a delivery ratio. An enormous amount of research works pay attention to solving the following two problems: whether to forward and how to forward. Therefore, forwarding metrics and forwarding strategies both play important roles in DTNs. In this paper, we consider a generalized random-waypoint model with heterogeneous nodes; the node's speed is regarded as the forwarding metric, which includes both short-term and long-term speed. Subsequently, we propose a theoretical, multicopy delegation forwarding based on short-term and long-term speed in DTNs (DFSL-T), which first determines a comprehensive mapping from short-term speed and long-term speed to the actual forwarding metric. Then, according to the forwarding metric and delegation forwarding strategy, DFSL-T utilizes some efficient nodes with higher forwarding metrics to assist in delivering messages, in order to improve the delivery ratio while reducing the forwarding cost. However, DFSL-T assumes that each node could achieve the average speeds of the others, which is impractical. In order to overcome this problem, we further propose a practical strategy (DFSL-P) through exchanging and evaluating the average speeds of each other. Finally, we conduct simulations based on the synthetic mobility pattern and real trace. The results show that compared with other multicopy forwarding strategies, DFSL-T and DFSL-P achieve higher forwarding efficiency, which is the result of delivery ratio divided by forwarding cost. [ABSTRACT FROM AUTHOR]

Summary: In the traffic monitoring system, the transportation department generates the traffic map to report the real‐time traffic conditions, so as to provide more efficient service for drivers. However, if the vehicle obtains the local traffic conditions that the driver is more concerned about from the remote server, it will consume a heavy bandwidth and incurs an increased response delay. Generating and broadcasting local traffic conditions through fog computation is a feasible method to reduce communication costs, and most existing traffic monitoring systems based on fog computation are implemented using Bilinear Pairing operations. In this paper, we propose Lightweight and Privacy‐preserving Traffic Monitoring (LPTM) scheme with Elliptic Curve Cryptosystem, an optimized Timed Efficient Stream Loss‐tolerant Authentication protocol is adopted to achieve efficient and secure communication, and we also use an identity‐based signature scheme with partial message recovery to effectively shorten the length of the fog node broadcast message. Detailed security proofs show that the requirements of security and privacy are all achieved, and better simulation performance is presented in both computation and communication overhead. [ABSTRACT FROM AUTHOR]

NDN is a band new Internet architecture, which aims to cope with the increasing growth of data traffic. NDN brings native support for consumer mobility due to its receiver-driven content retrieval model. However, producer mobility is still a challenging issue, which needs additional mechanisms to improve the data availability during the producer’s movement. Therefore, this paper proposed a scalable mobility-management mechanism, which further extends the stateful forwarding plane of NDN to support producer mobility. The mechanism built a temporary forwarding path on the name-based NDN forwarding plane through network terminals and designed a buffering and retransmission mechanism to support both delay-tolerant and delay-sensitive data traffic. Finally, this paper set up a comprehensive simulation environment in ndnSIM for the proposed evaluation and comparison against the existing classes of solutions. The simulation results show that the proposed can fully support producer mobility in the wireless environment. When the speed is 30 m/s, the packet loss rate is only 3.0 %, and the average transmission delay is 352.1 ms. Additionally, the additional consumption required to support producer mobility is reduced by 49.18 % compared to the comparison scheme. [ABSTRACT FROM AUTHOR]

Efficient mobility management solutions are essential to provide users with seamless connectivity and session continuity during movement. However, user mobility was not envisaged as one of the early Internet's use cases due to the early adoption of destination based routing and the assumption that end-nodes are static. This has become a critical hinder for providing efficient mobility support. This paper presents the challenges, drivers, and solutions that aim to overcome the drawbacks of current mobility management approaches. Furthermore, it introduces a promising solution that builds on emerging path-based forwarding architectures that identify network links rather than end nodes. Delivery path information is stored inside the packet while forwarding is achieved by performing a simple set membership test rather than the current destination-based routing approach. Mobility management in these architectures simply requires partial recomputation of the delivery path allowing for efficient mobility support over an optimal path. Evaluation results show significant cost savings in terms of delivery paths and end-to-end packet delay when using a path forwarding architecture. [ABSTRACT FROM AUTHOR]

In this paper, we study the potential of using the metric of Age of Information (AoI) for enhancing delay-tolerant routing protocols. The latter have been proposed for alleviating the impact of long roundtrip time in networks operating in harsh environments, e.g., in distributed applications deployed in a desert/sparsely populated area without infrastructure, a space network, etc. Delay-tolerant routing protocols can prevent excessive packet timer expiration, but do not provide any packet delivery time guarantee. Thus, they are unsuitable for time-sensitive applications that are more intensely desired nowadays in the next generation networking applications. By incorporating AoI into the operation of delay-tolerant routing protocols, we aim at devising routing protocols that can cope with both long propagation times and challenges related to time-sensitivity in packet delivery. More specifically, in this work, we modify the operation of a well-known delay-tolerant routing protocol, namely FRESH, to make AoI-based packet forwarding decisions, aiming at achieving specific delay guarantees regarding the end-to-end delivery time. We investigate the advantages and disadvantages of such an approach compared to the traditional FRESH protocol. This work serves as a cornerstone for successfully demonstrating the potential of exploiting AoI in delay-tolerant routing and its applications. [ABSTRACT FROM AUTHOR]

The use of Internet of Things (IoT) applications become dominant in many systems. Its on-chip data processing and computations are also increasing consistently. The battery enabled and low leakage memory system at subthreshold regime is a critical requirement for these IoT applications. The cache memory designed on Static Random-Access Memory (SRAM) cell with features such as low power, high speed, and process tolerance are highly important for the IoT memory system. Therefore, a process tolerant SRAM cell with low power, improved delay and better stability is presented in this research paper. The proposed cell comprises 11 transistors designed with symmetric approach for write operations and single ended circuit for read operations that exhibits an average dynamic power saving of 43.55% and 47.75% for write and 35.59% and 36.56% for read operations compared to 6 T and 8 T SRAM cells. The cell shows an improved write delay of 26.46% and 37.16% over 6 T and 8T and read delay is lowered by 50.64% and 72.90% against 6 T and 10 T cells. The symmetric design used in core latch to improve the write noise margin (WNM) by 17.78% and 6.67% whereas the single ended separate read circuit improves the Read Static Noise Margin (RSNM) by 1.88x and 0.33x compared to 6 T and 8T cells. The read power delay product and write power delay product are lower by 1.94x, 1.39x and 0.17x, 2.02x than 6 T and 8 T cells respectively. The lower variability from 5000 samples validates the robustness of the proposed cell. The simulations are carried out in Cadence virtuoso simulator tool with Generic Process Design Kit (GPDK) 45 nm technology file in this work. [ABSTRACT FROM AUTHOR]

Opportunistic ad hoc networks are characterized by intermittent and infrastructure-less connectivity among mobile nodes. Because of the lack of up-to-date network topology information and frequent link failures, geographic routing utilizes location information and adopts the store–carry–forward data delivery model to relay messages in a delay-tolerant manner. This paper proposes a message-forwarding policy based on movement patterns (MPMF). First, one- and two-hop location information in a geographic neighborhood is exploited to select relay nodes moving closer to a destination node. Message-forwarding decisions are made by referring to selected relay nodes' weight values obtained by calculating the contact frequency of each node with the destination node. Second, when relays in the vicinity of a message-carrying node are not qualified due to the sparse node density and nodal motion status, the destination's movement and the location information of a one-hop relay are jointly utilized to improve the message-forwarding decision. If the one-hop relay is not closer to the destination node or moving away from it, its centrality value in the network is used instead. Based on both synthetic and real mobility scenarios, the simulation results show that the proposed policy performs incomparable efforts to some typical routing policies, such as Epidemic, PRoPHETv2, temporal closeness and centrality-based (TCCB), transient community-based (TC), and geographic-based spray-and-relay (GSaR) routing policies. [ABSTRACT FROM AUTHOR]

In this paper, a joint optimization of link scheduling, routing and replication for delay-tolerant networks (DTNs) has been studied. The optimization problems for resource allocation in DTNs are typically solved using dynamic programming which requires knowledge of future events such as meeting schedules and durations. This paper defines a new notion of approximation to the optimality for DTNs, called snapshot approximation where nodes are not clairvoyant, i.e., not looking ahead into future events, and thus decisions are made using only contemporarily available knowledges. Unfortunately, the snapshot approximation still requires solving an NP-hard problem of maximum weighted independent set (MWIS) and a global knowledge of who currently owns a copy and what their delivery probabilities are. This paper proposes an algorithm, Max-Contribution (MC) that approximates MWIS problem with a greedy method and its distributed online approximation algorithm, Distributed Max-Contribution (DMC) that performs scheduling, routing and replication based only on locally and contemporarily available information. Through extensive simulations based on real GPS traces tracking over 4,000 taxies and 500 taxies for about 30 days and 25 days in two different large cities, DMC is verified to perform closely to MC and outperform existing heuristically engineered resource allocation algorithms for DTNs. [ABSTRACT FROM AUTHOR]

Densification through small cells and caching in base stations have been proposed to deal with the increasing demand for Internet content and the related overload on the cellular infrastructure. However, these solutions are expensive to install and maintain. Instead, using vehicles acting as mobile caches might represent an interesting alternative. In our work, we assume that users can query nearby vehicles for some time, and be redirected to the cellular infrastructure when the deadline expires. Beyond reducing costs, in such an architecture, through vehicle mobility, a user sees a much larger variety of locally accessible content within only few minutes. Unlike most of the related works on delay tolerant access, we consider the impact on the user experience by assigning different retrieval deadlines per content. In our paper, we provide the following contributions: (i) we model analytically such a scenario; (ii) we formulate an optimization problem to maximize the traffic offloaded while ensuring user experience guarantees; (iii) we propose two variable deadline policies; (iv) we perform realistic trace-based simulations, and we show that, even with low technology penetration rate, more than 60 percent of the total traffic can be offloaded which is around 20 percent larger compared to existing allocation policies. [ABSTRACT FROM AUTHOR]

Opportunistic networks are self-organizing networks that do not require a complete path between the source node and the destination node as it uses encounter opportunities brought by nodes movement to achieve network communication. Opportunistic networks routing algorithms are numerous and can be roughly divided into four categories based on different forwarding strategies. The Prophet routing algorithm is an important routing algorithm in opportunistic networks. It forwards messages based on the encounter probability between nodes, and has good innovation significance and optimization potential. However, the Prophet routing algorithm does not consider the impact of the historical throughput of the node on message transmission, nor does it consider the impact of the encounter duration between nodes on message transmission. Therefore, to improve the transmission efficiency of opportunistic networks, this paper based on the Prophet routing algorithm, fuses the impact of the historical throughput of the node and the encounter duration between nodes on message transmission at the same time, and proposes the Prophet_TD routing algorithm based on the historical throughput and the encounter duration. This paper uses the Opportunistic Networks Environment v1.6.0 (the ONE v1.6.0) as the simulation platform, controls the change of running time and the number of nodes respectively, conducts simulation experiments on the Prophet_TD routing algorithm. The simulation results show that compared to the traditional Prophet routing algorithm, on the whole, the Prophet_TD routing algorithm has a higher message delivery rate and a lower network overhead rate, and its average latency is also lower when node density is large. [ABSTRACT FROM AUTHOR]

The IPv6 routing protocol for low-power and lossy networks (RPL) is the standard routing protocol for IPv6 based low-power wireless personal area networks (6LoWPANs). In RPL protocol, DODAG information object (DIO) messages are used to disseminate routing information to other nodes in the network. A malicious node may eavesdrop DIO messages of its neighbor nodes and later replay the captured DIO many times with fixed intervals. In this paper, we present and investigate one of the severe attacks named as a non-spoofed copycat attack, a type of replay based DoS attack against RPL protocol. It is shown that the non-spoofed copycat attack increases the average end-to-end delay (AE2ED) and packet delivery ratio of the network. Thus, to address this problem, an intrusion detection system (IDS) named CoSec-RPL is proposed in this paper. The attack detection logic of CoSec-RPL is primarily based on the idea of outlier detection (OD). CoSec-RPL significantly mitigates the effects of the non-spoofed copycat attack on the network's performance. The effectiveness of the proposed IDS is compared with the standard RPL protocol. The experimental results indicate that CoSec-RPL detects and mitigates non-spoofed copycat attack efficiently in both static and mobile network scenarios without adding any significant overhead to the nodes. To the best of our knowledge, CoSec-RPL is the first RPL specific IDS that utilizes OD for intrusion detection in 6LoWPANs. [ABSTRACT FROM AUTHOR]

In many wireless networks, such as ad hoc, sensor, and delay-tolerant networks, the destination node is determined from the source node by the flooding process. Flooding efficiency is important for nodes, because they are driven by limited batteries. In this paper, we propose a simple flooding scheme to transmit a route request (RREQ) message based on the remaining power of its own node without using control packets and complex calculations. We applied the proposed scheme to ad hoc on-demand distance vector (AODV) routing protocol as an example and carried out computer simulations (ns3). The results showed that the proposed scheme was superior to conventional schemes in static and mobile scenarios. First, we showed the limit of node density that causes the decrease of throughput in the proposed scheme and that the proposed scheme was superior in terms of energy efficiency (bits/J), including throughput and energy consumption. Next, as the number of flooding times is made uniform in the proposed scheme, all nodes will have almost the same battery replacement time. As a result, when the nodes are static, the lifetime in the proposed scheme is longer than that in the conventional scheme. [ABSTRACT FROM AUTHOR]

Caching-enabled device-to-device (D2D) networks have the potential to make mobile users directly fetch requested files from nearby users, resulting in low network delay. In addition, user mobility can increase the communication chances among different users, and therefore, the network delay can be further effectively reduced by proper designing the caching strategy. In this paper, mobility-aware caching strategies in D2D networks are studied to minimize the network delay. Specifically, based on the inter-contact user mobility model, the expression of the average file delivery delay is analytically obtained. Considering the limited cache capacity, a delay minimization cache placement problem considering the user mobility is investigated. To optimally solve this nonlinear integer programming problem, we reformulate it as a multistage decision problem. According to the recursive relationship between adjacent stages, dynamic programming is adopted to obtain the optimal mobility-aware caching strategy stage-by-stage. Furthermore, to lower the complexity, we also demonstrate that the original problem can be recasted as a monotone submodular function maximization problem over a matroid constraint. Then, a low-complexity greedy mobility-aware caching strategy with $(1-1/e)$ -optimality performance guarantee is put forward. Numerical results show that, in the scenario with high user mobility, the file delivery delay can be reduced by 47% with our proposed mobility-aware caching strategy, as compared with the most popular caching. Furthermore, the superiority of the proposed caching strategy is verified by real-world data set. [ABSTRACT FROM AUTHOR]

The dramatic growth of mobile application usage has posed great pressure on application developers to better manage their backend capacity. Rule-based or schedule-based auto-scaling mechanisms have been proposed, but it is difficult or expensive to frequently adjust the backend capacity to track the burstiness of mobile traffic. In this paper, we explore a fundamentally different approach. Instead of scaling the backend in line with the mobile traffic, we smooth out traffic profiles to reduce the required backend capacity and increase its utilization. Our proposed solution, called Razor, is inspired by two key insights on mobile traffic. First, mobile traffic exhibits high short-term fluctuations but steady long-term trend, so that we may temporarily delay user requests and periodically adapt backend capacity based on the predicted traffic volume. Second, user requests have different priorities: while some requests are urgent (e.g., sending a message), some are delay-tolerant (e.g., changing the profile photo) and can be postponed without much influence on the user experience. Based on these observations, our design features a two-tier architecture: on a long timescale, Razor predicts future traffic using machine learning algorithms and plans the optimal backend capacity to minimize the budget with performance guarantee; on a short timescale, Razor schedules which requests to delay and by how much time to delay according to their delay tolerance. We implement a fully-functional prototype of Razor, and evaluate its performance with both real and synthetic traces. Extensive experimental results show that Razor can effectively help mobile application developers reduce their backend cost while guaranteeing the user experience. [ABSTRACT FROM AUTHOR]

Two of the most dominant challenges in post disaster emergency resource allocation are: 1) understanding the exact utility, i.e., exigency, of emergency resources and 2) collecting and transmitting the need for these resources to the control station from where resources are allocated. Measuring the utility of resources with precision becomes tricky in a dynamic post disaster scenario, where demands are constantly evolving and supplies trickle in at an uncertain rate. Moreover, collection and transmission of resource needs of far-flung areas are easier said than done owing to the post disaster disruption of communication infrastructure. These result in the ad-hoc allocation of emergency resources to the shelters. In this paper, we first derive a utility function for dynamically enumerating the shelter specific utility of each emergency resource. Subsequently, we propose an opportunistic knowledge sharing scheme for gathering and disseminating resource needs to the control station using a smartphone-based delay tolerant network. Finally, based on these opportunistically transmitted needs, we formulate a utility driven optimal resource allocation model which minimizes overall resource deficit and total resource deployment time. The proposed system optimally assigns constrained emergency resources to different shelters, so that high-utility resources are deployed fast. The effectiveness of the proposed system is evaluated using ONE simulator and LINGO optimization modeling tool. Exhaustive simulation is done to evaluate the comparative performance of our system with a number of competing schemes. Results show that our system outperforms all these schemes in a fully connected scenario. It is also observed that even in an intermittently connected environment, the performance of our system is almost at par with the competing schemes. [ABSTRACT FROM AUTHOR]

This paper studies data forwarding by using the node's spatial information in mobile social networks (MSNs). Specifically, we partition the 2D space into several grids, and periodically record the nodes' staying within each grid to extract their movement history summaries. Then, nodes' movement history summaries are used to compare their forwarding abilities in the single-copy scenario. In the multiple-copy scenario, we first address the dependent data forwarding path problem, i.e., different copies will reach the same relay with good forwarding ability, and thus the advantage of multiple-copy cannot be fully utilized. To avoid this, we jointly consider the nodes' forwarding abilities and their movement trajectories to perform copy distribution. Therefore, the potential overlap of multiple copies is minimized. In addition, we propose an extended scheme, which periodically records the nodes' transaction in grids. It improves the performance at the cost of more computation and storage consumption. Through extensive trace-driven experiments, proposed algorithms achieve good performance in different scenarios. [ABSTRACT FROM AUTHOR]

With the development of vehicle communication technologies, Vehicular Ad Hoc Networks (VANETs) through short distance communication technology achieve communication in Vehicle to Vehicular (V2V) and Vehicular to Infrastructure (V2I), which provides the basis for the implementation of application. However, the privacy and security of vehicle and message forwarding are vulnerably attacked by attacker due to the dynamic network topology. To address the problems, a Socially Aware Security Message Forwarding Mechanism (SASMF) based on trust assessment is proposed in this paper. Firstly, the pseudonym is used to protect the privacy of the vehicles, and the exchange entropy is as a measure to evaluate the exchange conditions of the pseudonym to avoid the continuous tracking of the vehicle by the attacker. Furthermore, according to the trust gradient, the message is forwarded in the form of multiple pieces of information to several relay vehicles and to the Application Provider (AP) through the Road Side Units (RSUs). Results show that the proposed mechanism can effectively improve the success rate of message forwarding and reduce the risk of message leakage and better protect the privacy of VANETs. [ABSTRACT FROM AUTHOR]

Due to the limited resource of Delay-Tolerant Network (DTN) nodes, in order to prolong their life cycles, the nodes would exhibit a "selfish" behavior, which is quite common in DTN, and will seriously affect the overall performance of the network. Targeting at these issues, to suppress such behavior and improve the overall performance of DTN, this paper proposed a DTN routing algorithm based on the auction price game, which converted the routing process into a data forwarding service auction process, and took the "prices" and the history data of the nodes as the main basis for the selection of data nodes. The experimental results showed that, compared with Epidemic algorithm and FC algorithm, the proposed algorithm showed good performance in time delay and cost ratio, which had well suppressed the "selfish" behavior of the nodes, and the proposed algorithm is a DTN routing algorithm with balanced performance. [ABSTRACT FROM AUTHOR]